Michigan State University

About: Michigan State University is a education organization based out in East Lansing, Michigan, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 60109 authors who have published 137074 publications receiving 5633022 citations. The organization is also known as: MSU & Michigan State.

The Rapid Rise of Supermarkets in Latin America: Challenges and Opportunities for Development

Abstract: Why are we writing, in the same article, about ‘supermarkets’ and ‘development’ in a region where 39% of the people are in poverty and 13% in absolute poverty (Echeverria, 1998)? Are not supermarkets niche players for rich consumers in the capital cities of the region? The answer is ‘no’; that traditional image is now a distant memory of the preliberalisation period before the 1990s. This theme issue of Development Policy Review shows that supermarkets are now dominant players in most of the agrifood economy of Latin America, having moved from a rough -estimate population-weighted average of 10-20% in 1990 to 50-60% of the retail sector in 2000. In one globalising decade, Latin American retailing made the change which took the US retail sector 50 years. The supermarkets, together with large-scale food manufacturers, have deeply transformed agrifood markets in the region. Many of those changes spell great challenges – even exclusion – for small farms and processing and distribution firms, but also potentially great opportunities. Development policy and programmes need to adapt to this radical change. The above findings are derived from the articles in this theme issue, the key points of which are compared in this overview article, and set in the context of background and other recent case literature. Earlier versions of the articles 1 were presented at the International Workshop ‘Concentration in the Processing and Retail Segments of the Agrifood System in Latin America, and its Effects on the Rural Poor’, held in November 2000 in Santiago, Chile, organised by the International Network for Research on Farming Systems (RIMISP) and funded by the Department for International Development (DFID) of the United Kingdom. The nine articles are on Argentina, Brazil, Chile, Costa Rica, and Mexico. They focus on the rise of supermarkets and large-scale food manufacturers over the 1990s to the present, and illustrate the effects of their rise on the dairy products and fresh fruit and vegetables (FFV) sectors. Dairy and FFV were chosen because of the interest development programmes have for these products: they are seen as good prospects for sma ll farms and firms because of their higher value-added and income-generation potential and their relative lack of economies of scale (compared with basic grains and

Student conceptions of natural selection and its role in evolution

Abstract: Pretests and posttests on the topic of evolution by natural selection were administered to students in a college nonmajors' biology course. Analysis of test responses revealed that most students understood evolution as a process in which species respond to environmental conditions by changing gradually over time. Student thinking differed from accepted biological theory in that (a) changes in traits were attributed to a need-driven adaptive process rather than random genetic mutation and sexual recombination, (b) no role was assigned to variation on traits within a population or differences in reproductive success, and (c) traits were seen as gradually changing in all members of a population. Although students had taken an average of 1.9 years of previous biology courses, performance on the pretest was uniformly low. There was no relationship between the amount of previous biology taken and either pretest or posttest performance. Belief in the truthfulness of evolutionary theory was also unrelated to either pretest or posttest performance. Course instruction using specially designed materials was moderately successful in improving students' understanding of the evolutionary process.

Machine learning in geosciences and remote sensing

Abstract: Learning incorporates a broad range of complex procedures. Machine learning (ML) is a subdivision of artificial intelligence based on the biological learning process. The ML approach deals with the design of algorithms to learn from machine readable data. ML covers main domains such as data mining, difficult-to-program applications, and software applications. It is a collection of a variety of algorithms (e.g. neural networks, support vector machines, self-organizing map, decision trees, random forests, case-based reasoning, genetic programming, etc.) that can provide multivariate, nonlinear, nonparametric regression or classification. The modeling capabilities of the ML-based methods have resulted in their extensive applications in science and engineering. Herein, the role of ML as an effective approach for solving problems in geosciences and remote sensing will be highlighted. The unique features of some of the ML techniques will be outlined with a specific attention to genetic programming paradigm. Furthermore, nonparametric regression and classification illustrative examples are presented to demonstrate the efficiency of ML for tackling the geosciences and remote sensing problems.

Role Conflict and Role Ambiguity: Integration of the Literature and Directions for Future Research

Abstract: Although research on role conflict and ambiguity has been extensive, there has been only moderate consistency in the focus and results of the research, while several areas of role conflict and ambiguity research are still relatively unexamined. This paper suggests that a framework for organizing the recent research may assist in consolidating the field and providing an understanding of where we are, what is left to be done and, therefore, direction for future role conflict and ambiguity research.